Overview

Dataset statistics

Number of variables11
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.5 KiB
Average record size in memory97.3 B

Variable types

Categorical5
Numeric6

Alerts

배출년도 has constant value ""Constant
배출월 has constant value ""Constant
지자체 시도명 has constant value ""Constant
지자체 시군구명 is highly overall correlated with 배출량(g) and 2 other fieldsHigh correlation
지자체코드 is highly overall correlated with 배출량(g) and 2 other fieldsHigh correlation
배출요일 is highly overall correlated with 배출량비율(%) and 1 other fieldsHigh correlation
배출량(g) is highly overall correlated with 배출횟수 and 2 other fieldsHigh correlation
배출량비율(%) is highly overall correlated with 배출요일 and 1 other fieldsHigh correlation
배출횟수 is highly overall correlated with 배출량(g) and 2 other fieldsHigh correlation
배출횟수비율(%) is highly overall correlated with 배출요일 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 10:43:50.596696
Analysis finished2023-12-10 10:43:57.590371
Duration6.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

배출년도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2020
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 100
100.0%

Length

2023-12-10T19:43:57.690441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:43:57.871172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 100
100.0%

배출월
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
4
100 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 100
100.0%

Length

2023-12-10T19:43:58.041701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:43:58.195145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 100
100.0%

배출일
Real number (ℝ)

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:43:58.328263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q17
median14
Q322
95-th percentile29
Maximum30
Range29
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.8334763
Coefficient of variation (CV)0.60920526
Kurtosis-1.2329291
Mean14.5
Median Absolute Deviation (MAD)8
Skewness0.16149815
Sum1450
Variance78.030303
MonotonicityNot monotonic
2023-12-10T19:43:58.505058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2 4
 
4.0%
8 4
 
4.0%
3 4
 
4.0%
10 4
 
4.0%
9 4
 
4.0%
1 4
 
4.0%
7 4
 
4.0%
6 4
 
4.0%
5 4
 
4.0%
4 4
 
4.0%
Other values (20) 60
60.0%
ValueCountFrequency (%)
1 4
4.0%
2 4
4.0%
3 4
4.0%
4 4
4.0%
5 4
4.0%
6 4
4.0%
7 4
4.0%
8 4
4.0%
9 4
4.0%
10 4
4.0%
ValueCountFrequency (%)
30 3
3.0%
29 3
3.0%
28 3
3.0%
27 3
3.0%
26 3
3.0%
25 3
3.0%
24 3
3.0%
23 3
3.0%
22 3
3.0%
21 3
3.0%

배출요일
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.06
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:43:58.685059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile7
Maximum7
Range6
Interquartile range (IQR)4

Descriptive statistics

Standard deviation1.9375086
Coefficient of variation (CV)0.47721886
Kurtosis-1.1334461
Mean4.06
Median Absolute Deviation (MAD)2
Skewness-0.077823914
Sum406
Variance3.7539394
MonotonicityNot monotonic
2023-12-10T19:43:58.920551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
5 17
17.0%
4 17
17.0%
6 14
14.0%
7 13
13.0%
1 13
13.0%
2 13
13.0%
3 13
13.0%
ValueCountFrequency (%)
1 13
13.0%
2 13
13.0%
3 13
13.0%
4 17
17.0%
5 17
17.0%
6 14
14.0%
7 13
13.0%
ValueCountFrequency (%)
7 13
13.0%
6 14
14.0%
5 17
17.0%
4 17
17.0%
3 13
13.0%
2 13
13.0%
1 13
13.0%

지자체코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
W01
30 
W02
30 
W03
30 
W04
10 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowW01
2nd rowW01
3rd rowW01
4th rowW01
5th rowW01

Common Values

ValueCountFrequency (%)
W01 30
30.0%
W02 30
30.0%
W03 30
30.0%
W04 10
 
10.0%

Length

2023-12-10T19:43:59.130050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:43:59.322609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
w01 30
30.0%
w02 30
30.0%
w03 30
30.0%
w04 10
 
10.0%

지자체 시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시
2nd row서울특별시
3rd row서울특별시
4th row서울특별시
5th row서울특별시

Common Values

ValueCountFrequency (%)
서울특별시 100
100.0%

Length

2023-12-10T19:43:59.520370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:43:59.681571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 100
100.0%

지자체 시군구명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로구
30 
중구
30 
용산구
30 
성동구
10 

Length

Max length3
Median length3
Mean length2.7
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종로구
2nd row종로구
3rd row종로구
4th row종로구
5th row종로구

Common Values

ValueCountFrequency (%)
종로구 30
30.0%
중구 30
30.0%
용산구 30
30.0%
성동구 10
 
10.0%

Length

2023-12-10T19:43:59.874139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:44:00.077643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 30
30.0%
중구 30
30.0%
용산구 30
30.0%
성동구 10
 
10.0%

배출량(g)
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4486380
Minimum423550
Maximum18991850
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:00.274759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum423550
5-th percentile467852.5
Q1576037.5
median3374975
Q35974037.5
95-th percentile14023015
Maximum18991850
Range18568300
Interquartile range (IQR)5398000

Descriptive statistics

Standard deviation4095570.4
Coefficient of variation (CV)0.91288978
Kurtosis1.9817854
Mean4486380
Median Absolute Deviation (MAD)2780750
Skewness1.4372955
Sum4.48638 × 108
Variance1.6773697 × 1013
MonotonicityNot monotonic
2023-12-10T19:44:00.543055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
555100 2
 
2.0%
3158000 1
 
1.0%
627100 1
 
1.0%
538800 1
 
1.0%
534950 1
 
1.0%
561800 1
 
1.0%
506550 1
 
1.0%
470500 1
 
1.0%
478700 1
 
1.0%
454200 1
 
1.0%
Other values (89) 89
89.0%
ValueCountFrequency (%)
423550 1
1.0%
433100 1
1.0%
454200 1
1.0%
454600 1
1.0%
463150 1
1.0%
468100 1
1.0%
470500 1
1.0%
477400 1
1.0%
478700 1
1.0%
484300 1
1.0%
ValueCountFrequency (%)
18991850 1
1.0%
15997350 1
1.0%
14235050 1
1.0%
14194050 1
1.0%
14064150 1
1.0%
14020850 1
1.0%
13945850 1
1.0%
13933600 1
1.0%
13508800 1
1.0%
13251400 1
1.0%

배출량비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3321
Minimum2.71
Maximum4.48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:00.808912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.71
5-th percentile2.91
Q13.0875
median3.23
Q33.5425
95-th percentile3.9435
Maximum4.48
Range1.77
Interquartile range (IQR)0.455

Descriptive statistics

Standard deviation0.3463352
Coefficient of variation (CV)0.10393902
Kurtosis1.0086129
Mean3.3321
Median Absolute Deviation (MAD)0.2
Skewness1.0271218
Sum333.21
Variance0.11994807
MonotonicityNot monotonic
2023-12-10T19:44:01.077298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.17 5
 
5.0%
3.01 4
 
4.0%
3.48 3
 
3.0%
3.23 3
 
3.0%
3.24 3
 
3.0%
3.31 3
 
3.0%
3.22 3
 
3.0%
3.06 3
 
3.0%
3.07 3
 
3.0%
2.91 3
 
3.0%
Other values (57) 67
67.0%
ValueCountFrequency (%)
2.71 1
 
1.0%
2.77 1
 
1.0%
2.88 1
 
1.0%
2.91 3
3.0%
2.92 1
 
1.0%
2.93 1
 
1.0%
2.94 1
 
1.0%
2.97 1
 
1.0%
2.98 1
 
1.0%
3.0 1
 
1.0%
ValueCountFrequency (%)
4.48 1
1.0%
4.34 1
1.0%
4.31 1
1.0%
4.04 1
1.0%
4.01 1
1.0%
3.94 1
1.0%
3.9 2
2.0%
3.84 1
1.0%
3.82 1
1.0%
3.79 2
2.0%

배출횟수
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3361.9
Minimum348
Maximum12852
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:01.350682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum348
5-th percentile369.45
Q1452.5
median2485.5
Q34700.5
95-th percentile10402.1
Maximum12852
Range12504
Interquartile range (IQR)4248

Descriptive statistics

Standard deviation2992.0472
Coefficient of variation (CV)0.88998696
Kurtosis1.2557074
Mean3361.9
Median Absolute Deviation (MAD)2055.5
Skewness1.2611399
Sum336190
Variance8952346.3
MonotonicityNot monotonic
2023-12-10T19:44:01.602572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
398 2
 
2.0%
433 2
 
2.0%
466 1
 
1.0%
395 1
 
1.0%
415 1
 
1.0%
420 1
 
1.0%
459 1
 
1.0%
396 1
 
1.0%
381 1
 
1.0%
351 1
 
1.0%
Other values (88) 88
88.0%
ValueCountFrequency (%)
348 1
1.0%
351 1
1.0%
355 1
1.0%
357 1
1.0%
359 1
1.0%
370 1
1.0%
381 1
1.0%
388 1
1.0%
391 1
1.0%
395 1
1.0%
ValueCountFrequency (%)
12852 1
1.0%
11186 1
1.0%
10490 1
1.0%
10481 1
1.0%
10442 1
1.0%
10400 1
1.0%
10281 1
1.0%
10057 1
1.0%
10041 1
1.0%
9750 1
1.0%

배출횟수비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3343
Minimum2.82
Maximum4.29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:44:01.844970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.82
5-th percentile2.948
Q13.17
median3.29
Q33.4725
95-th percentile3.782
Maximum4.29
Range1.47
Interquartile range (IQR)0.3025

Descriptive statistics

Standard deviation0.27778073
Coefficient of variation (CV)0.083310058
Kurtosis1.3982687
Mean3.3343
Median Absolute Deviation (MAD)0.15
Skewness0.91952927
Sum333.43
Variance0.077162131
MonotonicityNot monotonic
2023-12-10T19:44:02.121755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.17 5
 
5.0%
3.21 4
 
4.0%
3.28 3
 
3.0%
3.51 3
 
3.0%
3.31 3
 
3.0%
3.23 3
 
3.0%
3.53 3
 
3.0%
3.37 3
 
3.0%
3.25 2
 
2.0%
3.29 2
 
2.0%
Other values (55) 69
69.0%
ValueCountFrequency (%)
2.82 1
1.0%
2.85 1
1.0%
2.88 1
1.0%
2.9 1
1.0%
2.91 1
1.0%
2.95 2
2.0%
2.99 1
1.0%
3.0 1
1.0%
3.01 1
1.0%
3.05 2
2.0%
ValueCountFrequency (%)
4.29 1
1.0%
4.21 1
1.0%
4.06 1
1.0%
3.93 1
1.0%
3.82 1
1.0%
3.78 1
1.0%
3.77 2
2.0%
3.72 2
2.0%
3.69 1
1.0%
3.68 1
1.0%

Interactions

2023-12-10T19:43:55.867258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:51.080507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:51.987720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:52.919327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:53.827157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:54.865781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:56.039805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:51.217087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:52.144012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:53.091779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:53.971337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:55.029552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:56.202676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:51.343053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:52.285513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:53.234279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:54.121624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:55.197646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:56.374031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:51.491474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:52.444137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:53.376820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:54.390919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:55.372445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:56.553779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:51.686965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:52.608150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:53.508522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:54.547130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:55.537982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:56.695007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:51.822680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:52.751182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:53.667473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:54.698765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:43:55.703372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:44:02.311228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배출일배출요일지자체코드지자체 시군구명배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
배출일1.0000.6280.0000.0000.0000.4670.0000.522
배출요일0.6281.0000.0000.0000.2380.5970.1230.570
지자체코드0.0000.0001.0001.0001.0000.3741.0000.403
지자체 시군구명0.0000.0001.0001.0001.0000.3741.0000.403
배출량(g)0.0000.2381.0001.0001.0000.8360.9470.791
배출량비율(%)0.4670.5970.3740.3740.8361.0000.5860.844
배출횟수0.0000.1231.0001.0000.9470.5861.0000.770
배출횟수비율(%)0.5220.5700.4030.4030.7910.8440.7701.000
2023-12-10T19:44:02.539412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지자체 시군구명지자체코드
지자체 시군구명1.0001.000
지자체코드1.0001.000
2023-12-10T19:44:02.702331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배출일배출요일배출량(g)배출량비율(%)배출횟수배출횟수비율(%)지자체코드지자체 시군구명
배출일1.000-0.093-0.1410.121-0.1530.0970.0000.000
배출요일-0.0931.000-0.117-0.520-0.115-0.5360.0000.000
배출량(g)-0.141-0.1171.0000.2220.9930.2080.9740.974
배출량비율(%)0.121-0.5200.2221.0000.2040.9370.2390.239
배출횟수-0.153-0.1150.9930.2041.0000.2270.9840.984
배출횟수비율(%)0.097-0.5360.2080.9370.2271.0000.2420.242
지자체코드0.0000.0000.9740.2390.9840.2421.0001.000
지자체 시군구명0.0000.0000.9740.2390.9840.2421.0001.000

Missing values

2023-12-10T19:43:57.225760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:43:57.482608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

배출년도배출월배출일배출요일지자체코드지자체 시도명지자체 시군구명배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
02020425W01서울특별시종로구31580003.0923213.15
12020436W01서울특별시종로구33006003.2324143.28
22020447W01서울특별시종로구32440003.1723343.17
32020451W01서울특별시종로구39841003.927073.68
42020462W01서울특별시종로구38479003.7626993.66
52020473W01서울특별시종로구32913003.2224833.37
62020484W01서울특별시종로구32492003.1823633.21
72020495W01서울특별시종로구32182503.1523713.22
820204106W01서울특별시종로구32891003.2224183.28
920204117W01서울특별시종로구32398003.1723643.21
배출년도배출월배출일배출요일지자체코드지자체 시도명지자체 시군구명배출량(g)배출량비율(%)배출횟수배출횟수비율(%)
902020425W04서울특별시성동구142350503.23104813.31
912020436W04서울특별시성동구135088003.07100413.17
922020447W04서울특별시성동구139458503.1797503.08
932020451W04서울특별시성동구189918504.31128524.06
942020462W04서울특별시성동구159973503.63111863.53
952020473W04서울특별시성동구139336003.17102813.25
962020484W04서울특별시성동구140208503.19104423.3
972020495W04서울특별시성동구140641503.19104003.28
9820204106W04서울특별시성동구132514003.01100573.18
992020414W01서울특별시종로구31356003.0724063.27